RNA Splicing Code Revealed

A fundamental breakthrough

Researchers have deciphered the code governing alternative RNA splicing, which allows living cells to use a limited number of genes to produce many different RNA messages.

In a paper appearing in the journal Nature, "Deciphering the Splicing Code," a team led by Brendan Frey and Benjamin Blencowe of the University of Toronto explains the code governing alternative splicing. The discovery could one day help predict or prevent diseases such as cancers and neurodegenerative disorders.

When the human genome was fully sequenced in 2004, approximately 20,000 genes were identified. However, living cells use those genes to generate a much richer and more dynamic source of instructions — hundreds of thousands of distinct genetic messages that direct most cellular activities. Frey likens this finding to "hearing a full orchestra playing behind a locked door, and then when you pry the door open, you discover only three or four musicians generating all that music."

To figure out how living cells generate vast diversity in their genetic information, Frey and postdoc Yoseph Barash developed a computer analysis method that finds 'codewords' hidden within the genome that constitute what is referred to as an 'RNA splicing code'. This code contains the rules governing how separate parts of a single precursor RNA message can be spliced together in different ways to produce a wide variety of messages ("messenger RNAs"). "For example, three neurexin genes can generate over 3,000 genetic messages that help control the wiring of the brain," says Frey.

"Previously, researchers couldn't predict how the genetic messages would be rearranged, or spliced, within a living cell," Frey said. "The splicing code that we discovered has been successfully used to predict how thousands of genetic messages are rearranged differently in many different tissues."

Frey and Blencowe attribute the success of their project to the close collaboration between the members of their team of computational and experimental biologists. "Understanding a complex biological system is like understanding a complex electronic circuit. Our team 'reverse-engineered' the splicing code using large-scale experimental data generated by the group," Frey said.